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Agriculture Data 
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- Data Categories
- Agriculture Data
- B2B Data
- Biometric Data
- Company Data
- Conservation Data
- Demographic Data
- Economic Data
- Environmental Data
- Geospatial Data
- Healthcare Data
- Individual Data
- Industry-Specific Data
- Internet of Things (IoT) Data
- Legal and IP Data
- People and Employment Data
- Political Data
- Psychology Data
- Real Estate Data
- Retail & Commerce Data
- Social Data
- Space Exploration Data
- Sports & Entertainment Data
- Web Data
Smart Cities
What Is Smart Cities Data?
A smart city is a city whose infrastructure and services have the ability to collect and share data. Smart cities data, therefore, refers to the data that make up or are generated by smart cities.
Why Is It Important to Have a Good Smart City System?
The purpose of this data is to improve city services for citizens. This includes crime detection as well as traffic, utilities, and waste management.
In essence, an effectively-run smart city keeps citizens and visitors safe while they go about their day. For instance, it can collect exact payment for utilities used while reducing waste at the city-wide level. It can even oversee traffic at the granular level with V2X technologies. Of course, the smart city model relies on individuals (for example, those with new cars enabled with V2X tech) to contribute data to the smart city ecosystem.
What Internal Data Should I Have for a Good Smart City System?
To create a smart city, you will need data on the city’s infrastructure, utilities and other service providers, city organizational structure, and population.
What External Data Is Essential for a Good System?
It can be hard to determine essential external smart cities data sources versus useful ones—particularly since each city has its own needs and budgets. However, some examples of essential external data sources include map/geospatial data, weather data, and traffic data.
What External Data May Prove Useful for a Good Smart Cities Data System?
Useful external data for smart cities may include events or open-source traffic databases like WikiRoutes. Above all, each city must make its own judgements on what data to include as useful.
What Are the Main Challenges of this Use Case?
Every city faces its own challenges in moving to a smart city model. However, some widely-used concerns include population increases and decreases (increases strain infrastructure whereas decreases remove revenue sources for smart cities), interoperability between various city services, and, of course, security.
Interesting Case Studies and Blogs to Look Into
Smart Cities Council Readiness Guide
BCG: The Risks and Rewards of Data Sharing for Smart Cities
Tangible Examples of Impact
Spending on smart city technology is expected to reach US$327 billion by 2025, up from US$96 billion in 2019, according to a new forecast from Frost & Sullivan.
The analyst company said an uncertain post-pandemic situation will compel cities to focus on developing collaborative, data-driven infrastructure for use in healthcare, public security services and more.
Artificial intelligence and data-driven solutions are expected to be in high demand, with growing opportunities for crowd analytics, open data dashboards and digital city services.
The Next Web: We currently have no smart cities — by 2025 there’ll be 26
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